Current chemical hazard testing procedures do not take into account the genetic diversity of the population that may be at risk of exposure; however, our recent data show that genetic differences between mouse inbred strains have a profound impact on time-, dose- and organ-specific effects of toxic agents. Thus, we hypothesize that the knowledge on the modes of action of toxic agents can be efficiently combined with advances in tissue engineering, in silico modeling, genetics and genomics to develop novel approaches that improve in vitro and in vivo chemical hazard testing paradigms, prioritize environmental agents for selection and increase throughput of screening in a biologically meaningful and sensible way. This application proposes to establish a partnership between environmental health scientists, biological engineers, chem- informaticians, biostatisticians and geneticists. This multidisciplinary team will apply an integrative, systems approach to: (1) Develop a 3D microscale mouse liver tissue bioreactor that can be applied to high- throughput screening of chemicals. This is a design-directed effort to produce a unique tool that can increase throughput of testing while reducing the number of animals; (2) To build, test and validate Quantitative Structure-Toxicity Relationship (QSTR) models that employ both chemical and biological descriptors of molecular structures and take into account genetic diversity between individuals. This aim is a discovery- driven approach that will produce a computational method for compound-prioritization based on the chemical structure, multi-dimensional toxicity data that includes -omics endpoints, and information on genetic diversity of the population; and (3) Validate a fiscally sensible in vivo and in vitro toxicity screening paradigm for a class of allylbenzene derivatives by producing knowledge anchored on the genetic variability present within the population. This aim will test the hypothesis that genetic variability among individuals is a major determinant in the toxic effects of chemical hazards and that the genetic basis for susceptibility can be successfully elucidated using a panel of mouse inbred strains. The partnership will be directed by Ivan Rusyn, M.D., Ph.D. (UNC Public Health) who is an environmental health scientist with experience in liver toxicology and mouse models of toxicity. Other Lead Investigators are: Linda Griffith, Ph.D. (Massachusetts Institute of Technology), a world-renowned researcher in the field of liver tissue engineering; Alex Tropsha, Ph.D., (UNC Pharmacy), a leader in the field of quantitative structure activity/toxicity relationship modeling; and David Threadgill, Ph.D. (UNC Medicine), a geneticist whose work pioneers the applications of mouse genetics into cancer research and toxicology. Collectively, this effort will lead to significant and timely advances in understanding the relationship between chemical identity and chemical hazard within a genetically diverse population. It will also illustrate how basic science in environmental health, genetics, chem-informatics and bioengineering can be combined to prevent human disease by improving our ability to extrapolate and translate findings from chemical testing to human populations and by informing regulatory decisions that limit exposures to disease-associated environmental agents. [unreadable] [unreadable] [unreadable]